Development of the Neuse Estuary Eutrophication Model: Background and Calibration

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Development of the Neuse Estuary Eutrophication
Model Background and Calibration

• By
• James D. Bowen
• UNC Charlotte

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Neuse River Estuary Model
Pamlico Sound
Applied Water Quality Modeling Research
Neuse Estuary
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Neuse River Estuary
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Facts About the Neuse River

• 3rd Largest River Basin in NC (6,234 mi2)
• 200 miles long, 3000 stream miles
• Estuary in lower 50 miles
• 1.5 million people in basin, mostly near
  headwaters
• Nutrient loading has doubled since 70s

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Neuse River Problems Algal Blooms
Blue-GreenAlgae Bloom near New Bern
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1997 Bottom Water DO Conc.
Neuse River Problems Low DO
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Low DO and Fish Kills 94-96
Cherry Point
Streets Ferry
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Water Quality Research Project

• MODMON MODeling and MONitoring
• Interdisciplinary Applied Research
• Water Quality and Biological Monitoring
• Water Quality Modeling to predict w.q.
  improvement (30 nutr. red.)

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Neuse EstuaryEutrophicationModel
Physical Processes
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Neuse EstuaryEutrophicationModel
Water Column Biological Processes
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Neuse EstuaryEutrophicationModel
Benthic/Water- Column Interactions
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Neuse Estuary EutrophicationModel
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Special Features of Modeling

• Unusually challenging system to model
• intermittent, weak stratification (wind driven)
• no strong tidal forcing
• sediments have important effects on nutrient and
  DO dynamics
• blooms of several different phytoplankton groups
  _at_ different times and places

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Neuse Estuary Eutrophication Model

• based upon 2-d laterally averaged model
  CE-Qual-W2
• Nutrient, phytoplankton, organic matter, DO model
• 3 phytoplankton groups (V.3)
• summer assemblage, diatoms, dinoflagellates

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W2 Phytoplankton Growth Model
1
T.R.M.
0
Topt
Temperature
m mmax min(m / mmax) T.R.M.
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W2 X-section Representation

• trapezoidal cross-sections for each segment

Layer 1
Layer 4
Sediment Compartments

• quasi-3d sediment/water-column interaction model

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W2 Sediment Submodel

• simple sediment diagenesis model
• 1 constituent Sediment organic carbon (SOC)
• SOC fate processes
• redistribution, decomposition
• SOD decomposition rate determines fluxes
• O2 demand, PO4 release, NH3 release
• N, P, S, Fe redox reactions not considered
• e.g. NH3/NO3, NO3/N2, SO4/H2S
• can simulate sediment clean-up

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1991 Simulation Description

• Time Period
• March 1 - September 27, 1991
• Boundary Data Frequency
• Daily Flow and NO3, monthly WQ
• Hydrodynamic Calibration Data
• hrly. water elevations, salinities, velocities _at_
  3 estuary stations
• WQ Calibration Data
• monthly mid-water nutrients, DO, chl-a _at_ 4
  estuary stations

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H2O N Inflows - 1991
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Inflow N/P molar ratio - 1991
Redfield Ratio
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Other Model Characteristics

• 62 horizontal segments, 18 layers
• execution time step 10 min.
• 2 branches Neuse Trent Rivers
• 12 tributaries 9 creeks, 3 WWTPs
• 16 state variables
• Boundary Conditions Flow _at_ Streets Ferry,
  Elevation _at_ Oriental

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Neuse Estuary Model Results Transport Model

• Water elevations
• time histories
• spectral analysis
• Salinity distributions
• time histories _at_ one segment
• animations

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Elevations _at_ Cherry Point
Observed
Model
March
April
May
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Water Level _at_ New Bern
MAE 0.1 m
Julian Day
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Elev. Fluctuations - Power Spectrum
Observed
_at_ Cherry Point n 0.020
Amplitude (m)
Model
Frequency (Cycles/day)
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Salinities _at_ Cherry Point
Model Surface
Observed Top Bottom
Salinity (ppth)
Model Bottom
May
Sep
Mar
July
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Modeled Salinities - September 1991
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1991 Predicted Salinities May - Sept. animation
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Neuse Estuary - 1991 Nitrogen
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Neuse Estuary - 1991 Chl-a Conc.s
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WQ Conditions Summary

• Seasonal/Spatial Trends
• nutrients decreasing downstream
• April mid-estuary phytoplankton bloom
• June upper-estuary phytoplankton bloom
• several pulses of high NOx conc. _at_ New Bern
• August high-flow event
• high nutrients, low chl-a _at_ New Bern
• high Sept. chl-a _at_ New Bern

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1991 WQ Simulations

• Single parameter displays
• Nitrate
• Phytoplankton
• Cumulative chl-a
• Multi-parameter display
• New Bern time history

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Modeled Nitrate - September 1991
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1991 Predicted Nitrates May - Sept. animation
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Modeled DO - September 1991
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1991 Predicted DO May - Sept. animation
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Modeled chl-a - September 1991
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1991 Predicted chl-a May - Sept. animation
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Water Quality Prediction - New Bern
0
Surface
Middle
6
.5
0
Surface
10
Middle
4
50
0
May
Sep
Mar
July
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Calibration Summary

• Transport Model
• elevation variations predicted within 0.1 m
• salinity variations within 2 ppth
• dynamics nicely represented
• Water Quality Model
• blooms of phytoplankton well represented
• seasonal variations also represented
• New Bern chl-a shows influence of physical
  processes

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Summary, continued

• Water Quality Model
• DO dynamics fit expectations based on 1997
  monitoring
• Overall model performance
• consistent with previous modeling efforts
• sufficient for water quality improvement
  predictions